Choosing the exponential function as the time decay function has improved some link prediction algorithms[1]}, [2]}, and it can be regarded as one of the information decay modes. Besides, scholars have been discussing the society as an information- and knowledge-based society. By giving an insight into them, information resources can be clarified with life cycle model[3]}, [4]}, [5]}. The life cycle phases consist of generation, institutionalization, maintenance, enhancement, and distribution. Inspired by this theory, we assume that the generation of new edges tends to remain active for a certain period of time, and then decay to a stable state. For example,
the 2022 Grammys song of the year Leave the door open, its Billboard chart history follows the above hypothesis that it remained popular (top five) for 14 weeks, then it was gradually losing its position in the following 25 weeks, finally it fell off the chart in week number 40. Based on this assumption, we find that the sigmoid function in neural network[6]} is accompanied with such properties. By parameterizing the sigmoid function, we obtain the adjusted sigmoid function (ASF), which satisfies the assumption, as the temporal information decay function. It can be divided into active state, decay state and stable state. The formal definition of ASF is as follows.
\(ASF(x) = \frac{\frac{1}{1 + exp\lbrace x/p - a\rbrace } + q}{q+1},\) 
